环境科学最新文献

{"title":"[Analysis of Influencing Factors of Regional Carbon Emissions in China Based on Emission Reduction Level Indexes].","authors":"Yu-Cong Jiang, Yan-Ying Li, Shun-Ping Wang, Yu-Xin Yang","doi":"10.13227/j.hjkx.202408126","DOIUrl":"https://doi.org/10.13227/j.hjkx.202408126","url":null,"abstract":"<p><p>China has put forward the strategic goal of achieving carbon peak by 2030 and carbon neutrality by 2060， and study of the CO₂ emission reduction potential is crucial for China and provincial regions to realize the dual-carbon goal. In this study， 30 provinces （autonomous regions and municipalities directly under the central government） in China are used as the research objects， and a regional carbon emission reduction potential evaluation system is constructed. Based on the BP neural network under the CRITIC coefficient of variation method， the provincial emission reduction index is calculated， combined with the cluster analysis of the differences in regional emission reduction potentials， and the SSA-XGBoost model is set up to investigate the factors influencing regional carbon emissions in China and their degree of influence. The results of the study include the following： ① The regional carbon emission reduction level index has a significant spatial correlation. The average carbon emission reduction value is higher in the southeastern coastal provinces， and the inland provinces with more backward economic development have more low values. ② China's 30 provincial-level regions are divided into four emission reduction potential categories， including Shandong， Guangdong， Hebei， Jiangsu， Zhejiang， Fujian， Henan， Hubei， Hunan， and Sichuan with good and excellent emission reduction potentials， which are the main driving forces for realizing the \"double carbon\" goal， and 14 provinces with average emission reduction potential. The degree of influence on carbon emissions has the following order： energy structure &gt; digital structure &gt; infrastructure structure &gt; industrial structure &gt; resource structure &gt; population structure &gt; economic structure. Energy structure as an influencing factor has the strongest potential to reduce carbon emissions in the industry category， infrastructure structure has a higher degree of influence in the optimization of the environment category， and population structure is more important than digital structure in the social category. The results show that China's carbon emission reduction level is characterized by uneven development regionally， cleaner energy， and a higher influence of social digitalization. To realize benign and efficient transformation and green development of the provinces and the country， it is suggested that the characteristics of provinces with strong emission reduction capacity should gradually be extended to the average and poorer provinces.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 9","pages":"5415-5427"},"PeriodicalIF":0.0,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145081867","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Characterization of Microplastics and Diazotrophic Community in Greenhouse Soils with Vegetable Planting Ages in Karst Areas].","authors":"Hui Zhao, Lu-Lu Zhang, Bin Bai, Xi-Ying Wang, De-Yan Li, Zhi-Yong Tan","doi":"10.13227/j.hjkx.202408117","DOIUrl":"https://doi.org/10.13227/j.hjkx.202408117","url":null,"abstract":"&lt;p&gt;&lt;p&gt;In recent years， microplastics （MPs） contamination in agroecosystems and its adverse effects on soil health and plants has attracted increasing concern. Biological nitrogen fixation is an important source of nitrogen for the agroecosystem， and soil fertility maintenance can be affected greatly by the diazotrophs. However， there are few studies on the evolution characteristics and interrelationships of MPs and diazotrophs in greenhouse vegetable fields with different planting years in karst areas. This study aimed to analyze the changes in MPs and diazotroph community in different planting years （1， 5， 10， and 12） in karst areas. The results showed that the contents of total nitrogen （TN）， ammonium nitrogen （NH&lt;sub&gt;4&lt;/sub&gt;&lt;sup&gt;+&lt;/sup&gt;-N）， and nitrate nitrogen （NO&lt;sub&gt;3&lt;/sub&gt;&lt;sup&gt;-&lt;/sup&gt;-N） increased with prolongation of growth. Soil urease （URE） and sucrase （SUC） activities first increased and then decreased with prolongation of growth， and the pH value， organic carbon （SOC）， available potassium （AK）， C/N， and catalase activities （CAT） of soils decreased with prolongation of growth. MPs were detected in all greenhouse vegetable field soil samples at concentrations ranging from （286.67±72.23） to（2 454.33±309.73） n·kg&lt;sup&gt;-1&lt;/sup&gt;， with a mean abundance of （1 518.58±174.03） n·kg&lt;sup&gt;-1&lt;/sup&gt;. The abundance of MPs increased with increase of planting years. MPs in greenhouse vegetable fields with different planting years had mostly small size （0?1 mm）， accounting for 55.59% of the distribution. The small size （0-0.1 mm） increased with increase of planting year. Fibers， fragments， and films were the main shapes of MPs， occupying 40.81%， 27.34%， and 23.74% of the MPs， respectively. The color was mainly transparent， accounting for 24.78% of MPs， and the most common polymer type was polypropylene， accounting for 20.83%. With increase in planting years in the greenhouse vegetable fields， the &lt;i&gt;nifH&lt;/i&gt; gene and diversity index α changed significantly， with the abundances of &lt;i&gt;nifH&lt;/i&gt; gene and diversity index α being promoted significantly to year 5 but being significantly inhibited after year 5. The dominant phyla in the soil diazotrophic community included mainly Pseudomonadota （48.60%） and Thermodesulfobacteriota （44.54%）. &lt;i&gt;Desulfuromonas&lt;/i&gt;， &lt;i&gt;Bradyrhizobium&lt;/i&gt;， &lt;i&gt;Citrifermentans&lt;/i&gt;， and &lt;i&gt;Azohydromonas&lt;/i&gt; were the dominant genera. After 5 years of planting， the abundances of Pseudomonadota， &lt;i&gt;Desulfuromonas&lt;/i&gt;，&lt;i&gt;Bradyrhizobium&lt;/i&gt;， and &lt;i&gt;Citrifermentans&lt;/i&gt; were significantly increased， but their relative abundances decreased with increase after planting year thereafter. The pH， SOC， NO&lt;sub&gt;3&lt;/sub&gt;&lt;sup&gt;-&lt;/sup&gt;-N， C/N， AK， NH&lt;sub&gt;4&lt;/sub&gt;&lt;sup&gt;+&lt;/sup&gt;-N， CAT， and MPs values were the main factors affecting the structure of the bacterial community. Partial least squares path modeling （PLS-PM） analysis showed that planting years have a significant inhibitory effect on the diazotrophic community due to enrichment of MPs. Thus， utilizing ","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 9","pages":"5985-5998"},"PeriodicalIF":0.0,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145082031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Construction of Urban Green Infrastructure Based on a Multi-scale and Multi-objective Approach in Ecologically Vulnerable Areas in the Upper Yellow River： A Case Study of the Four Lakes Hydrographic Net in Ningxia].","authors":"Wen-Hao Cheng, Cai-Hong Ma","doi":"10.13227/j.hjkx.202407288","DOIUrl":"https://doi.org/10.13227/j.hjkx.202407288","url":null,"abstract":"<p><p>The construction of urban green infrastructure （UGI）， especially in ecologically vulnerable areas of the upper Yellow River， is an effective tool to ensure ecological protection and promote high-quality development of the Yellow River Basin. Taking the Four Lakes Hydrographic Net in Shizuishan City as an example， this study focused on identifying the important sources of UGI by morphological spatial pattern analysis （MSPA）， which integrated both regional and inter-regional perspectives. Additionally， the UGI networks were constructed based on multiple objectives， using the minimum cumulative resistance （MCR） model， and the UGI network stability， integrating centrality and connectivity perspectives， was subsequently evaluated. The study produced several results： ① Nineteen important sources， with an area of 105.07 km²， were identified in the Four Lakes Hydrographic Net， and 41 important sources， with an area of 433.10 km²， were recognized in Shizuishan City. Both the intrinsic importance of each patch and the connectivity between patches were considered in the integration of UGI sources. ② Based on a trade-off analysis and synthesis of each single object， lengths of 7.79 km of critical corridors， 9.42 km of ordinary corridors， and 29.89 km of fragile corridors did not need to be maintained. Furthermore， 5.51 km of ordinary corridors and 25.78 km of fragile corridors did not need to be upgraded. The overall connectivity index （<i>O</i>_G） value of the UGI network under the multi-objective approach exceeded the same index under the single-object approach and the simple overlay of an individual object. It not only ensured the integrity of the landscape pattern but also saved costs of landscape construction. The method of multiple scales and objectives in UGI planning reveals the diverse requirements for urban landscape security and sustainability. It can be applied to carry out urban landscape protection and restoration according to different geographical conditions， and it also provides a valuable example for addressing similar areas.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 9","pages":"5872-5882"},"PeriodicalIF":0.0,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145081983","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Emission Reduction Mechanism of Carbon Trading Policy and Industry Heterogeneity： Evidence from Inter-Provincial Industrial Sub-sectors].","authors":"Xin-Xin Yu, Ming-Dong Jiang, Jia-Nan Li, Ze-Peng Wu","doi":"10.13227/j.hjkx.202408049","DOIUrl":"https://doi.org/10.13227/j.hjkx.202408049","url":null,"abstract":"<p><p>Clarifying the heterogeneity of the driving mechanism of the carbon trading market for different industries can provide more detailed theoretical references for the design of targeted emission reduction programs. Based on three-dimensional panel data of 27 subdivided industrial sectors in 30 provinces in China from 2007 to 2019， a multi-period double-difference model is constructed to empirically test the industrial emission reduction effect of the carbon trading market pilot policy and its mechanism of action. The empirical results show that carbon trading policies can effectively reduce the carbon emissions of the industrial sectors， with their impact showing a certain lag effect. Specifically， its impact coefficients on production scale， technological innovation， and carbon emission intensity are -0.156， 0.377， and -0.251， respectively. This indicates that although the industrial sector achieves emission reduction under the carbon trading market system by upgrading the level of technological innovation and lowering the intensity of carbon emissions， it also compresses the production scale to a certain extent. In addition， there is an antagonistic relationship between growth and emission reduction targets. Further research showed that carbon trading policies have a greater reduction effect on sectors with low capital returns， such as ferrous metal mining and dressing and non-metallic mineral products， as well as sectors with low technology intensity such as textiles， garments， footwear， leather and its products， and coal mining and washing. Furthermore， they have a better quality improvement effect on carbon-intensive sectors such as electricity， gas， water production and supply， and ferrous metal smelting and rolling processing. Based on these conclusions， this paper proposes relevant policy recommendations for improving the carbon market system according to targeted industrial technology and emission characteristics.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 9","pages":"5503-5511"},"PeriodicalIF":0.0,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145081672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Evaluation of Carbon Sequestration Service Flow in Minjiang River Basin for Supply and Demand Synergy].","authors":"Hong-Xia Dai, Hui-Li Xie, Ling-Xiu Chen, Yang-Yi Gao, Jiao Zhang, Meng-Jie Xu, Xin-Ke Wang, Sheng-Long Liu, Si-Tao Chen, Xing-Zhao Liu","doi":"10.13227/j.hjkx.202408154","DOIUrl":"https://doi.org/10.13227/j.hjkx.202408154","url":null,"abstract":"<p><p>Guided by the carbon peaking and carbon neutrality goals， clarifying the transmission mechanisms of carbon sequestration service flow （CSSF） in river basins is crucial for promoting sustainable development. To enhance the coordination between carbon sequestration service supply and demand in the Minjiang River Basin， this study quantified the current supply and demand status and proposed a comprehensive evaluation framework for carbon sequestration service flow. The framework incorporated the breakpoint formula， field strength model， and topographic distribution index to explore the spatial transmission characteristics of carbon sequestration service in both horizontal and vertical dimensions， ultimately proposing differentiated strategies for optimizing carbon sequestration service flow. The results are as follows： ① The supply of carbon sequestration service in the Minjiang River Basin exhibits a spatial distribution pattern of \"low along the riverbanks and high in the mountainous areas，\" while the demand shows a pattern of \"high in coastal regions and low in inland areas.\" ② Overall， the basin is in a state of surplus supply， whereas urban development areas show a deficit. Notably， 45.4% of the regions in the basin show a mismatch between supply and demand， with areas of deficit exhibiting spatial aggregation. ③ Among the input areas in the Minjiang River Basin， 72.7% can receive effective carbon sequestration service supply from other counties， whereas Jinan District， Mawei District， and Changle District in the southeast are unaffected by carbon sequestration service flow. ④ From the high-terrain mountainous area to the low-terrain flat area， the V-level potential CSSF gradually loses its dominant position， with 86.5% of the CSSF in the Minjiang River Basin provided from higher-grade topographic counties to lower-grade topographic counties. The research findings provide scientific references for ecological protection， restoration， and compensation mechanisms in the Minjiang River Basin.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 9","pages":"5930-5940"},"PeriodicalIF":0.0,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145081743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Ecological Zoning of Urban Agglomeration of Central Guizhou Through Ecological Resilience].","authors":"Wen-Bin Zhang, Xu Zhou, Wen-Ling Yuan, Guang-Yan Ran, Guo-Feng Rao","doi":"10.13227/j.hjkx.202408294","DOIUrl":"https://doi.org/10.13227/j.hjkx.202408294","url":null,"abstract":"<p><p>Ecological resilience plays a crucial role in maintaining system security and protecting the environment when urban systems are subjected to human activities and natural disasters， and ecological zoning based on ecological resilience （ER） has great significance for effective management of regional structure and improvement of ecological environment. Here， taking the urban agglomeration of central Guizhou as an example， we constructed an analytical framework of ecological potential （EP）-ecological elasticity （EE）-ecological stability （ES） to assess the ER level of the study area from 2000 to 2023 using a GIS grid， the unit-area-equivalent-factor method， elasticity coefficient， and landscape pattern index and also outlined the three ecological zones and established differentiated zoning strategies. The results of the study follow： ① The ER value showed an increasing trend during 2000-2010， it decreased with the largest change， which was most obviously affected by a significant decrease of stability， during 2010-2020， and then showed a slow increasing trend during 2020-2023. The distribution pattern of ER can be described as \"low in the center and high in the periphery.\" ② For different ER levels， there were three types of zones： key restoration zones distributed in the Nanming District in Guiyang， Anshun， and the Guian New Area， source protection zones distributed in the north-central part of the county and townships， and moderately developed zones distributed in Dushan County of Qiannan and Congjiang County of Qiandongnan Prefecture， among other areas. ③ Optimization of the spatial layout of corresponding restoration results was carried out to promote regional development and resource utilization.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 9","pages":"5883-5894"},"PeriodicalIF":0.0,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145081679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Spatiotemporal Evolution Characteristics and Influencing Factors of Carbon Emissions from Construction Industry in Western China].","authors":"Xin-Sheng Zhang, Da-Wen Nie, Zhang-Zheng Chen, Run-Zhou Wang, Jia Su","doi":"10.13227/j.hjkx.202408170","DOIUrl":"https://doi.org/10.13227/j.hjkx.202408170","url":null,"abstract":"<p><p>As the second largest source of carbon emissions in China and the industry with the greatest emission reduction potential， the construction industry is an important industry through which to achieve the goal of \"double carbon\". Systematic studies on the carbon emission of the construction industry in western China are scarce and fail to reveal the characteristics of spatiotemporal evolution and the nonlinear relationship between complex factors completely. Firstly， the Slope value， Theil index， Moran's <i>I</i> index， and gravity shift model were applied to explore the spatial and temporal patterns and carbon emission changes from the construction sector in the western area of China during the period from 2003 to 2022. Then， the random forest model and SHAP method were used to identify the key factors affecting carbon emissions within this sector. The study produced several important results： ① Carbon emissions in the construction sector in the western region show a clear upward trend and significant regional differences. The average annual contribution rate within the region is 70.8%， which is much higher than the inter-regional contribution rate of 29.2%， and the average contribution rate in the southwest region is 54.7%. ② The mean value of the global Moran's <i>I</i> index of carbon emissions is 0.141， and all values pass the 90% test. There is a spatial autocorrelation， and the local areas show a trend of \"high-high concentration\" and \"low-low concentration\". ③ The carbon emission center of gravity fluctuated within a small range in the border area of Sichuan， Gansu， and Shaanxi provinces， and there was a cyclical swing trend. ④ The urbanization rate， year-end permanent resident population， added value of the construction industry， and added value of the tertiary industry have a notable influence on carbon emissions in the construction sector. In consideration of the above results， this study recommends taking effective actions in five key areas： enhance coordinated carbon emission management across regions， guide the rational flow of population and industrial optimization， promote green buildings and low-emission technologies， enhance the development strategy of the urbanization and construction sector， and foster coordinated growth of the service and construction industries. These measures will help mitigate the increase in carbon emissions in the construction sector of western China and support the sustainable development of the regional economy.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 9","pages":"5475-5489"},"PeriodicalIF":0.0,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145081715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Impact of New Urbanization on Total Factor Productivity of Carbon].","authors":"Xiao-Xian Zhu, Yan-Wei Wang, Jiang-Tao Chi, Fei-Wu Ren, Yi Huang","doi":"10.13227/j.hjkx.202407317","DOIUrl":"https://doi.org/10.13227/j.hjkx.202407317","url":null,"abstract":"<p><p>Improving total factor productivity of carbon （TFPC） is an important way to promote the green and low-carbon transformation of the economy and help achieve carbon emission peak and carbon neutrality goals. Therefore， exploring the impact of new-type urbanization on TFPC has great research significance. Based on the inter-provincial panel data of China from 2010 to 2021， TFPC was calculated using the super-efficiency EBM （epsilon-based measure） model of undesirable output. On this basis， the linear effect， nonlinear effect， and spatial spillover effect of new urbanization on TFPC were empirically tested by constructing a fixed effect model， threshold effect model， MMQR model， and spatial Durbin model. The study produced several interesting results： ① TFPC showed an overall increasing trend， but there were regional differences with the distribution characteristics of eastern &gt; national &gt; central &gt; western. ② New urbanization can significantly promote TFPC， and this conclusion remains valid after a series of robustness and endogeneity tests. ③ New-type urbanization has a significant nonlinear effect on TFPC. On one hand， new-type urbanization has a double threshold effect on TFPC. After new-type urbanization crosses the threshold values of 0.459 and 0.514， its increasing effect on TFPC is also gradually enhanced. On the other hand， as the level of TPFC increases， the impact of new-type urbanization on TFPC also increases. ④ New urbanization has a significant spatial spillover effect on TFPC. It not only contributes to the improvement of TFPC in the province but also has a positive impact on the improvement of TFPC in neighboring provinces through the spatial spillover effect.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 9","pages":"5512-5523"},"PeriodicalIF":0.0,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145081767","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Source Apportionment and Pollution Risk Assessment of Heavy Metals in Sediments of Huixian Wetland Based on PMF and APCS-MLR Models].","authors":"Tao Liu, Li-Na Shen, Shi Yu, Jin-Fu Qin","doi":"10.13227/j.hjkx.202407084","DOIUrl":"https://doi.org/10.13227/j.hjkx.202407084","url":null,"abstract":"<p><p>Based on the analysis of sediment samples from 14 sites in the Huixian Wetland， the content characteristics of eight heavy metals （Cu， Pb， Cd， Cr， Zn， Ni， Hg， and As） were investigated. The geoaccumulation index and potential ecological risk index were employed to assess the risks of these heavy metals. Correlation analysis， cluster analysis， absolute principal component scores-multiple linear regression （APCS-MLR）， and positive matrix factorization （PMF） were used in combination to identify and quantify the pollution sources and their contributions. The results are as follows： ① The average concentrations of all eight heavy metals exceeded background values， with Cd surpassing the screening values specified in the Soil Environmental Quality - Risk Control Standard for Soil Contamination of Agricultural Land （GB 15618-2018）. ② The geoaccumulation index evaluation indicated that Cd falls into the category of moderate pollution， Zn falls into the category of slight to moderate pollution， Hg， Ni， Cr， and Pb are categorized as slight pollution， and As and Cu are considered unpolluted. ③ The potential ecological risk index assessment revealed that Cd （245.91） poses a very high ecological risk， Hg （134.59） poses a high ecological risk， and other elements pose slight ecological risks. The mean comprehensive ecological risk index for the study area is 433.33， indicating a strong overall potential ecological risk. ④ APCS-MLR identified four pollution sources： agricultural sources， natural and agricultural sources， atmospheric deposition and domestic sources， and unidentified sources （transportation and agricultural sources）， with contribution rates of 33.16%， 15.75%， 9.50%， and 41.59%， respectively. PMF identified three pollution sources： atmospheric deposition and domestic sources， natural and agricultural sources， and transportation and agricultural sources， with contribution rates of 21.92%， 35.24%， and 42.84%， respectively.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 9","pages":"6024-6036"},"PeriodicalIF":0.0,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145081942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Land Cover Simulation and Carbon Stock Assessment in Huainan City Based on FLUS- InVEST Model].","authors":"Hai-Yue Zheng, Lei Wang, Tao Wei, Xin-Xin Qi, Yue Chen","doi":"10.13227/j.hjkx.202409033","DOIUrl":"https://doi.org/10.13227/j.hjkx.202409033","url":null,"abstract":"<p><p>To explore the impact of land use change on carbon storage, taking Huainan City as an example, the future land use simulation （FLUS） model was used to simulate the spatial distribution of land use in 2030 under the inertia development scenario, farmland protection scenario, and ecological priority scenario. By combining this result with the integrated valuation of ecosystem services and trade-offs （InVEST） model, the carbon storage of the three scenarios in 1990, 2000, 2010, 2020, and 2030 was estimated. The study produced the following results： ① The main land type in Huainan City is cropland, which accounts for more than 75% of the total area. From 1990 to 2020, the area of cropland, grassland, and forest land in Huainan City continued to decrease, while the area of construction land continued to increase. The main land type transfer was the conversion of cropland to construction land. Compared with the other scenarios, the farmland protection scenario can better promote the increase of farmland area and effectively suppress the expansion of construction land. ② From 1990 to 2020, the carbon storage in Huainan City decreased by 8.29×10⁵ t, with a continuous decreasing trend. Cropland was the main carbon reservoir in Huainan City, and the conversion of cropland to construction land was the main reason for the decrease in carbon storage in Huainan City. ③ The carbon stocks in Huainan City under the 2030 inertia development scenario, cropland protection scenario, and ecological priority scenario are 50 766×10³, 50 822.21×10³, and 50 597.95×10³ t, respectively. The carbon storage decreases compared to the level in 2020 under the three scenarios, among which the cropland protection scenario has the most significant inhibitory effect on the reduction of carbon storage. In the future, prioritizing the protection of cropland should be considered.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 8","pages":"4754-4764"},"PeriodicalIF":0.0,"publicationDate":"2025-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144856545","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}